Search engine optimization method based on big data and readable storage medium

Abstract

The invention relates to the technical field of search engine optimization, in particular to a search engine optimization method based on big data and a readable storage medium. The method comprises the steps of analyzing market and user demands, determining innovation keywords, positioning projects or products, including AI and big data analysis, so as to improve the innovation and competitiveness of the products or services, collecting technical application effect data, establishing a continuous monitoring mechanism, and tracking the effects of all steps. Iterative optimization is carried out according to market changes and user feedback, and a closed loop is formed. According to the method and the device, the purpose of comprehensively improving the search engine optimization effect is achieved, and particularly, keyword ranking improvement, flow increase, user experience improvement, mobile equipment adaptation optimization and continuous iteration optimization of strategies are achieved.

Description

Technical Field

[0001] The present application relates to the technical field of search engine optimization, and in particular to a search engine optimization method based on big data and a readable storage medium. Background Art

[0002] Search engine optimization (SEO) is an important part of Internet marketing. It optimizes website content and structure to improve the ranking of websites in search engines, thereby attracting more traffic and potential customers. With the rapid development of Internet technology, SEO has evolved from simple keyword stacking to a highly data-driven and intelligent process. Enterprises and personal website managers are increasingly relying on SEO to improve online visibility and brand influence, which not only helps to increase website traffic, but also improves user satisfaction and conversion rate. In existing SEO practices, commonly used methods include keyword research and layout, content creation and optimization, link building, and user experience improvement. Specifically, keyword research is usually completed through manual analysis and tool assistance to determine the target keywords and distribute them reasonably in various parts of the website; content creation relies on a professional editing team to generate high-quality, original articles, and use formats such as title tags and lists to optimize content structure; link building is mainly through the construction of internal and external links to enhance the authority and relevance of the website; in terms of user experience, it is through the optimization of web design, interaction methods and response time to improve the user's access experience. However, traditional SEO methods have some obvious shortcomings. For example, keyword research often lacks depth and breadth, and it is difficult to fully cover potential related words; the content creation and optimization process is time-consuming, and it is difficult to maintain long-term consistency and high quality; link building channels are limited, and it is difficult to continuously obtain high-quality external links; user experience optimization is often limited to superficial changes, and it is impossible to fundamentally improve user satisfaction and loyalty. These problems limit the maximization of SEO effects, making it difficult for websites to stand out in fierce competition. Therefore, a more systematic and intelligent SEO method is urgently needed to comprehensively improve the website's search performance and user experience. Summary of the invention

[0003] The purpose of this application is to overcome the above technical problems and provide "a search engine optimization method based on big data and a readable storage medium" A search engine optimization method based on big data, comprising: S1: determining innovative keywords through market and user demand analysis to position a project or product; S2: creating high-quality content based on the keywords determined in S1 and optimizing it to improve user appeal and search engine ranking; S3: collecting data by analyzing user behavior on products or content, understanding user needs and preferences, and providing a basis for subsequent link strategies and data analysis; S4: formulating link strategies based on the user behavior data collected in S3 to enhance the network visibility and user engagement of the content, while collecting link effect data; S5: integrating S1 to S All data collected in S4 are deeply analyzed to identify trends and problems, and keywords, content, links and user experience strategies are adjusted to improve the overall effect; S6: Based on the analysis results of S5, the user experience on mobile devices is optimized, the page loading speed is improved, and good performance on mobile devices is ensured, and the performance data after optimization is collected; S7: Explore and apply the latest technologies, including AI and big data analysis, to enhance the innovation and competitiveness of products or services, and collect data on the effect of technology application; S8: Establish a continuous monitoring mechanism to track the effect of all steps, and iterate and optimize according to market changes and user feedback to form a closed loop. By adopting the above technical solutions, this method can comprehensively improve the effect of search engine optimization. Specifically, through market and user demand analysis, innovative keywords are determined to ensure the diversity and accuracy of keywords for project or product positioning, and improve the ranking and traffic of the website in search engines. Based on the keywords determined in S1, high-quality content is created and optimized to improve user appeal and search engine ranking, improve the appeal of content and user experience, and enhance user stay time and interaction frequency. By analyzing user behavior on products or content, collecting data, understanding user needs and preferences, and providing a basis for subsequent link strategies and data analysis, the authority and credibility of the website are increased, and the trust of search engines is further improved. According to the user behavior data collected in S3, link strategies are formulated to enhance the network visibility and user engagement of the content, and link effect data is collected at the same time. Through in-depth mining of user behavior, the interactive design and content presentation of the website are optimized, and user satisfaction is significantly improved. Integrate all data collected from S1 to S4, conduct in-depth analysis, identify trends and problems, and adjust keywords, content, links and user experience strategies to improve the overall effect. Make SEO strategies more flexible and efficient, and be able to quickly adapt to market changes and user needs. Based on the analysis results of S5, optimize the user experience on mobile devices, improve page loading speed, ensure good performance on mobile devices, and collect optimized performance data to ensure good performance of the website on various devices and improve the access experience of mobile users.Explore and apply the latest technologies, including AI and big data analysis, to enhance the innovation and competitiveness of products or services, while collecting data on the effects of technology applications. Advanced technologies such as AI are introduced to improve the automation and intelligence level of optimization. Establish a continuous monitoring mechanism to track the effects of all steps, iterate and optimize according to market changes and user feedback, and form a closed loop to ensure the continuous improvement and optimization of the entire SEO strategy, forming a complete closed loop system. Preferably, the analysis of market and user needs to determine innovative keywords and position the project or product includes the following steps: S11: Semantic keyword analysis: Use NLP tools to deeply analyze the semantic association of keywords, identify potential synonyms and related words, and build a comprehensive keyword library; S12: Keyword trend prediction: Use AI technology to predict keyword trends and dynamically adjust keyword strategies; S13: Keyword layout optimization: Reasonably distribute keywords in the meta tags, URLs, and content of the website to ensure that keywords are naturally integrated and avoid stacking; S14: Keyword effect monitoring and adjustment: Regularly evaluate the ranking and traffic of keywords, adjust keyword strategies according to the results, and form a closed loop. By adopting the above technical solutions, through market and user demand analysis, innovative keywords are determined, and the project or product positioning can effectively improve the coverage and accuracy of keywords, and enhance the search visibility and traffic of the website. Specifically, using NLP tools for semantic keyword analysis can identify more potential related words and build a more comprehensive keyword library; using AI technology to predict keyword trends, dynamically adjust keyword strategies, and ensure that keywords always meet market demand; reasonably distribute keywords in the meta tags, URLs, and content of the website to avoid excessive stacking and improve the natural integration of keywords; regularly evaluate the ranking and traffic of keywords, and adjust strategies in time according to data results to form an effective closed-loop management, thereby continuously improving SEO results. Preferably, the creation of high-quality content based on the keywords determined in S1 and optimization to improve user appeal and search engine rankings include the following steps: S21: AI-assisted content creation: combining AI tools and professional editors to generate high-quality, highly original content to ensure the accuracy and attractiveness of the content; S22: Content structure optimization: using title tags, lists, paragraphs, etc. to make the content structure clear, easy for search engines to understand, and at the same time improve user experience; S23: Content personalization: using AI to analyze user preferences, optimize content form and style, and provide personalized content; S24: Content effect monitoring and optimization: evaluating the content reading volume, sharing volume and user feedback, and optimizing content strategies based on the results to form a closed loop.By adopting the above technical solutions, AI-assisted content creation can generate high-quality, highly original content, ensuring the accuracy and attractiveness of the content; content structure optimization makes the content structure clearer, which is easier for search engines to understand and improve user experience; content personalization uses AI to analyze user preferences, optimize content form and style, and provide content that better meets user needs; content effect monitoring and optimization evaluates the content reading volume, sharing volume and user feedback, and timely adjusts the content strategy to form a closed loop, ensuring the effectiveness and continuous improvement of the content strategy. Preferably, the method of analyzing the user's behavior on the product or content, collecting data, understanding the user's needs and preferences, and providing a basis for subsequent link strategies and data analysis includes the following steps: S31: Intelligent optimization of internal links: Automatically identify and optimize the internal link structure through algorithms to ensure that the link logic between the internal pages of the website is clear; S32: Improve the quality of external links: Use big data analysis to evaluate the quality and relevance of external links to ensure that the acquired links come from authoritative and relevant websites; S33: Link construction channel exploration: Explore new link construction channels, such as industry forums, social media, etc., to enhance the authority of the website; S34: Link effect monitoring and adjustment: Monitor the source and quality of the link, adjust the link strategy according to the results, and form a closed loop. By adopting the above technical solution, the rationality of the internal link structure of the website can be significantly improved, the link logic between the internal pages can be ensured to be clear, and the user's navigation experience can be enhanced. At the same time, the quality and relevance of external links are evaluated through big data analysis to ensure that the acquired links come from authoritative and relevant websites, further enhancing the authority of the website. In addition, exploring new link construction channels, such as industry forums, social media, etc., can help expand the influence and popularity of the website. Finally, by continuously monitoring the source and quality of the link, and adjusting the link strategy according to the results, a closed-loop management is formed to ensure the effectiveness and sustainability of the link strategy. Preferably, the link strategy is formulated according to the user behavior data collected in S3 to enhance the network visibility and user engagement of the content, and the link effect data is collected at the same time, including the following steps: S41: Personalized recommendation system: Based on the user's historical behavior and preferences, personalized content recommendations are provided to increase user stickiness; S42: User behavior modeling: Using big data to analyze the user's behavior patterns on the website, optimize the website layout and content, and improve user satisfaction; S43: AI predicts user behavior: Using AI to predict user behavior and optimize the user experience in advance; S44: User behavior monitoring and optimization: Continuously monitor user behavior, optimize the user experience strategy according to the results, and form a closed loop. By adopting the above technical solution, the personalized recommendation system can provide content recommendations that are more in line with the user's interests based on the user's historical behavior and preferences, thereby increasing the user's stickiness and residence time. User behavior modeling uses big data to analyze the user's behavior patterns on the website, optimize the website's layout and content, and improve user satisfaction and interactive experience.AI predicts user behavior and can identify possible user behavior patterns in advance, optimize user experience in a timely manner, and improve user satisfaction and loyalty. User behavior monitoring and optimization continuously monitors user behavior data, continuously adjusts and optimizes user experience strategies based on analysis results, and forms a closed-loop optimization process to ensure continuous improvement and enhancement of user experience. Preferably, the integration of all data collected in S1 to S4, in-depth analysis, identification of trends and problems, adjustment of keywords, content, links and user experience strategies to improve the overall effect includes the following steps: S51: Real-time data analysis: Use real-time data analysis tools to quickly respond to market changes and user needs and adjust SEO strategies; S52: Predictive analysis: Use machine learning algorithms to predict future search trends and user behavior, and optimize website content and structure in advance; S53: Strategy effect monitoring and iteration: Regularly evaluate the effectiveness of SEO strategies, including keyword rankings, traffic, conversion rates and other indicators, adjust strategies based on the results, and form a closed loop. By adopting the above technical solutions, real-time data analysis can quickly respond to market changes and user needs, adjust SEO strategies in a timely manner, and improve the flexibility and adaptability of strategies; predictive analysis uses machine learning algorithms to accurately predict future search trends and user behaviors, optimize website content and structure in advance, and enhance the foresight of strategies; strategy effect monitoring and iteration regularly evaluates the effectiveness of SEO strategies, including key indicators such as keyword rankings, traffic, and conversion rates, and adjusts strategies based on the evaluation results to ensure continuous optimization and effectiveness of strategies. Preferably, the analysis results based on S5 optimize the user experience on mobile devices, improve page loading speed, and ensure good performance on mobile devices, while collecting optimized performance data, including the following steps: S61: Responsive design: ensure that the website can provide a consistent and excellent user experience on different devices; S62: Page speed optimization: optimize images, compress code, use CDN, etc., to improve page loading speed; S63: Mobile optimization effect monitoring and adjustment: monitor the user experience and page loading speed on mobile devices, optimize mobile strategies based on the results, and form a closed loop. By adopting the above technical solutions, responsive design ensures that the website can provide a consistent and high-quality user experience on different devices. Page speed optimization significantly improves page loading speed by optimizing images, compressing codes, and using CDN, thereby improving user access satisfaction and retention rate. At the same time, the mobile optimization effect monitoring and adjustment mechanism can monitor the user experience and page loading speed on mobile devices in real time, optimize mobile strategies in a timely manner based on data feedback, form a closed-loop management, and further enhance the effect of mobile optimization.Preferably, the exploration and application of the latest technologies, including AI and big data analysis, to enhance the innovation and competitiveness of products or services, while collecting technology application effect data includes the following steps: S71: AI generates meta descriptions: using AI technology to automatically generate attractive meta descriptions to increase click-through rates; S72: Intelligent content updates: based on real-time data analysis, automatically update content to ensure the timeliness and relevance of website content; S73: Technology application effect monitoring and optimization: evaluate the application effects of AI and innovative technologies, adjust technical strategies based on the results, and form a closed loop. By adopting the above technical solutions, AI generates meta descriptions that can significantly increase the click-through rate of web pages and attract more users to visit the website; intelligent content updates ensure the timeliness and relevance of website content, and improve user satisfaction and stickiness; the technology application effect monitoring and optimization mechanism enables continuous adjustment of technical strategies based on actual results to ensure the continued effectiveness and innovation of SEO optimization methods. Preferably, the establishment of a continuous monitoring mechanism, tracking the effects of all steps, iterative optimization according to market changes and user feedback, and the formation of a closed loop includes the following steps: S81: SEO effect monitoring: regularly evaluate the effects of SEO strategies, including indicators such as keyword rankings, traffic, and conversion rates; S82: Strategy iteration optimization: according to the monitoring results, continuously optimize the SEO strategy to ensure the innovation and effectiveness of the strategy; S83: Overall strategy effect monitoring and iteration: comprehensively evaluate the overall effect of the SEO strategy, and iterate the strategy according to the results to form a closed loop. By adopting the above technical solution, comprehensive monitoring and continuous optimization of SEO strategies can be achieved. Specifically, the effects of SEO strategies are regularly evaluated, including key indicators such as keyword rankings, traffic, and conversion rates to ensure the effectiveness and innovation of the strategy; according to the monitoring results, the SEO strategy is continuously adjusted and optimized to keep it in the best state at all times; at the same time, the overall effect of the SEO strategy is comprehensively evaluated, and the strategy is iterated according to the actual situation to form a closed-loop management, thereby comprehensively improving the search engine performance and user satisfaction of the website. A readable storage medium, the storage medium stores a computer program, and the computer program is executed by a processor as any one of the search engine optimization methods based on big data.By adopting the above technical solution, the readable storage medium can store and execute the search engine optimization method based on big data, including determining innovative keywords through market and user demand analysis, positioning for projects or products, creating high-quality content based on the keywords determined in S1, and optimizing it to improve user appeal and search engine rankings, collecting data by analyzing user behavior on products or content, understanding user needs and preferences, providing a basis for subsequent link strategies and data analysis, formulating link strategies based on user behavior data collected in S3, enhancing the network visibility and user engagement of content, and collecting link effect data at the same time, integrating all data collected in S1 to S4, and conducting in-depth Analyze, identify trends and problems, adjust keywords, content, links and user experience strategies to improve overall results, optimize user experience on mobile devices based on S5 analysis results, improve page loading speed, ensure good performance on mobile devices, and collect optimized performance data, explore and apply the latest technologies, including AI and big data analysis, to enhance the innovation and competitiveness of products or services, collect technology application effect data and establish a continuous monitoring mechanism to track the effects of all steps, iterate and optimize according to market changes and user feedback, form a closed loop, and other aspects, so as to comprehensively improve the website's search engine ranking and user experience, and ensure the effectiveness and sustainability of SEO strategies.

[0004] In summary, this application includes at least one of the following beneficial technical effects: 1. By analyzing the market and user needs, determining innovative keywords, positioning the project or product, especially semantic keyword analysis, keyword trend prediction and keyword layout optimization, it is possible to more accurately capture and utilize potential keywords, dynamically adjust keyword strategies, and effectively improve the ranking and traffic of the website in search engines. 2. Based on the keywords determined in S1, high-quality content is created and optimized to improve user appeal and search engine rankings. Combined with AI-assisted content creation, content structure optimization and content personalization, it can not only generate high-quality and original content, but also optimize the content form and style according to user preferences, significantly improving the appeal of the content and user satisfaction. 3. By analyzing user behavior on products or content, collecting data, understanding user needs and preferences, and providing a basis for subsequent link strategies and data analysis, through intelligent optimization of internal links, improvement of external link quality and exploration of link construction channels, a richer and more authoritative link network can be built, enhancing the authority and relevance of the website, and further improving search engine rankings and user trust. BRIEF DESCRIPTION OF THE DRAWINGS

[0005] Figure 1 It is a flow chart of a search engine optimization method based on big data in an embodiment of the present application.

[0006] Figure 2It is a flowchart of the sub-steps of step S1 in the embodiment of the present application.

[0007] Figure 3 It is a flowchart of the sub-steps of step S1 in the embodiment of the present application.

[0008] Figure 4 It is a flowchart of the sub-steps of step S1 in the embodiment of the present application.

[0009] Figure 5 It is a flowchart of the sub-steps of step S1 in the embodiment of the present application.

[0010] Figure 6 It is a flowchart of the sub-steps of step S1 in the embodiment of the present application.

[0011] Figure 7 It is a flowchart of the sub-steps of step S1 in the embodiment of the present application.

[0012] Figure 8 It is a flowchart of the sub-steps of step S1 in the embodiment of the present application.

[0013] Fig. 9 It is a flowchart of the sub-steps of step S1 in the embodiment of the present application. DETAILED DESCRIPTION

[0014] The following will combine with the accompanying drawings to clearly and completely describe the technical solutions in the embodiments of the present invention. The described embodiments are only possible technical implementations of the present invention, and not all implementations are possible. Those skilled in the art can fully combine the embodiments of the present invention to obtain other embodiments without creative work, and these embodiments are also within the scope of protection of the present invention. The inventors of the present application have found that the existing search engine optimization methods lack systematicity and innovation, and cannot effectively improve the search performance and user experience of the website. For this reason, the present application mainly adopts the following search engine optimization method based on big data, which achieves the effect of comprehensively improving the search performance and user experience of the website. The present application is further described in detail below. Example 1 refers to Figure 1The embodiment of the present application provides a search engine optimization method based on big data, which includes the following aspects: determining innovative keywords through market and user demand analysis to position the project or product (S1); creating high-quality content based on the keywords determined in S1 and optimizing it to improve user appeal and search engine ranking (S2); collecting data by analyzing user behavior on products or content, understanding user needs and preferences, and providing a basis for subsequent link strategies and data analysis (S3); formulating link strategies based on the user behavior data collected in S3 to enhance the network visibility and user engagement of the content, and collecting link effect data at the same time (S4); Combine all the data collected in S1 to S4, conduct in-depth analysis, identify trends and problems, adjust keywords, content, links and user experience strategies to improve overall results (S5), optimize the user experience on mobile devices based on the analysis results of S5, improve page loading speed, ensure good performance on mobile devices, and collect optimized performance data (S6), explore and apply the latest technologies, including AI and big data analysis, to enhance the innovation and competitiveness of products or services, and collect technology application effect data (S7), establish a continuous monitoring mechanism, track the effects of all steps, perform iterative optimization based on market changes and user feedback, and form a closed loop (S8). These aspects work together to achieve the effect of comprehensively improving website search performance and user experience. S1: Determine innovative keywords through market and user demand analysis, and provide reference for project or product positioning Figure 2Specifically, through market and user demand analysis, innovative keywords are determined, and the positioning of projects or products includes the following steps: S11: Semantic keyword analysis: Use NLP tools such as NLTK, spaCy, etc. to deeply analyze the semantic association of keywords, identify potential synonyms and related words, and build a comprehensive keyword library. For example, for the keyword "resort" in the tourism industry, related words such as "hotel", "inn", and "homestay" can be identified through NLP tools. S12: Keyword trend prediction: Use AI technology such as Google Trends, TrendyTopic, etc. to predict keyword trends and dynamically adjust keyword strategies. For example, if it is predicted that "family travel" will become a hot topic, the keyword strategy can be adjusted in advance to increase the frequency of use of related keywords. S13: Keyword layout optimization: Reasonably distribute keywords in the meta tags, URLs, and content of the website to ensure that keywords are naturally integrated and avoid stacking. For example, keywords can be reasonably embedded in the title, first paragraph, and end of the article to increase keyword density while ensuring the fluency of the content. S14: Keyword effect monitoring and adjustment: Regularly evaluate the ranking and traffic of keywords, adjust keyword strategies according to the results, and form a closed loop. For example, you can use tools such as SEMrush and Ahrefs to monitor keyword performance and adjust keywords that do not meet the standards in a timely manner. S2: Based on the keywords identified in S1, create high-quality content and optimize it to increase user appeal and search engine rankings. Figure 3Specifically, based on the keywords determined in S1, creating high-quality content and optimizing it to improve user appeal and search engine rankings include the following steps: S21: AI-assisted content creation: Combine AI tools and professional editors to generate high-quality, original content to ensure the accuracy and appeal of the content. For example, AI writing tools such as GPT-3 and Jasper can be used, combined with the experience of professional editors, to generate high-quality articles on "family travel destination recommendation". S22: Content structure optimization: Use title tags, lists, paragraphs, etc. to make the content structure clear, easy for search engines to understand, and improve user experience. For example, you can use title tags such as H1, H2, and H3 to clearly present the "family travel destination recommendation" article in paragraphs, making it easier for readers to understand and search engines to crawl. S23: Content personalization: Use AI to analyze user preferences, optimize content form and style, and provide personalized content. For example, you can push the latest content related to "family travel destination recommendation" based on the user's historical browsing records and interests and hobbies to improve user stickiness. S24: Content effect monitoring and optimization: Evaluate the reading volume, sharing volume and user feedback of the content, optimize the content strategy based on the results, and form a closed loop. For example, you can use tools such as Google Analytics to analyze the performance of the "family travel destination recommendation" article and adjust the content strategy based on user feedback and data. S3: By analyzing user behavior on products or content, collect data, understand user needs and preferences, and provide a basis for subsequent linking strategies and data analysis Figure 4Specifically, by analyzing the user's behavior on the product or content, collecting data, understanding user needs and preferences, and providing a basis for subsequent link strategies and data analysis, the following steps are included: S31: Intelligent optimization of internal links: Automatically identify and optimize the internal link structure through algorithms to ensure that the link logic between the internal pages of the website is clear. For example, you can use tools such as Link Explorer to analyze the internal link structure of the website, optimize the weight distribution of internal links, and ensure that the links between the "Family Travel Destination Recommendation" page and other related pages are more reasonable. S32: Improvement of external link quality: Use big data analysis to evaluate the quality and relevance of external links to ensure that the links obtained are from authoritative and relevant websites. For example, you can use tools such as Moz Link Explorer and Ahrefs to analyze the quality of external links and give priority to high PR value travel websites for link exchange. S33: Link building channel exploration: Explore new link building channels, such as industry forums, social media, etc., to enhance the authority of the website. For example, you can obtain more external links by participating in travel forum discussions and publishing high-quality social media content. S34: Link effect monitoring and adjustment: Monitor the source and quality of links, adjust the link strategy according to the results, and form a closed loop. For example, you can use tools such as SEMrush and Ahrefs to regularly check the performance of external links and adjust low-quality links in a timely manner. S4: Based on the user behavior data collected in S3, formulate a link strategy to enhance the network visibility and user engagement of the content, and collect link performance data for reference Figure 5Specifically, according to the user behavior data collected in S3, a link strategy is formulated to enhance the network visibility and user engagement of the content, and the link effect data is collected at the same time, including the following steps: S41: Personalized recommendation system: Based on the user's historical behavior and preferences, personalized content recommendations are provided to increase user stickiness. For example, recommendation algorithms such as Collaborative Filtering and Content-Based Filtering can be used to push the latest content related to "family travel destination recommendation" according to the user's historical browsing records and interests. S42: User behavior modeling: Use big data to analyze the user's behavior patterns on the website, optimize the website layout and content, and improve user satisfaction. For example, tools such as Google Analytics and Mixpanel can be used to analyze the user's click path, dwell time, and bounce rate, and optimize the design and content layout of the "family travel destination recommendation" page. S43: AI predicts user behavior: Use AI to predict user behavior and optimize the user experience in advance. For example, machine learning models such as Random Forest and XGBoost can be used to predict user behavior patterns and make corresponding optimization measures in advance, such as loading relevant recommended content in advance when users browse the "family travel destination recommendation" page. S44: User behavior monitoring and optimization: Continuously monitor user behavior, optimize the user experience strategy based on the results, and form a closed loop. For example, you can use heat map tools such as Hotjar and Crazy Egg to analyze users' click hotspots and scrolling behaviors, and optimize the user experience of the "Family Travel Destination Recommendations" page based on the data. S5: Integrate all the data collected from S1 to S4, conduct in-depth analysis, identify trends and problems, and adjust keywords, content, links, and user experience strategies to improve the overall effect. Figure 6Specifically, all data collected in S1 to S4 are integrated for in-depth analysis, trends and problems are identified, and keywords, content, links, and user experience strategies are adjusted to improve the overall effect. The following steps are included: S51: Real-time data analysis: Use real-time data analysis tools to quickly respond to market changes and user needs and adjust SEO strategies. For example, tools such as Google Data Studio and Tableau can be used to monitor the data performance of the "Family Travel Destination Recommendation" page in real time and adjust SEO strategies in a timely manner. S52: Predictive analysis: Use machine learning algorithms to predict future search trends and user behaviors and optimize website content and structure in advance. For example, time series prediction models such as ARIMA and LSTM can be used to predict future search trends and user behaviors and make corresponding preparations in advance, such as optimizing the content of the "Family Travel Destination Recommendation" page before the peak season. S53: Strategy effect monitoring and iteration: Regularly evaluate the effectiveness of SEO strategies, including indicators such as keyword rankings, traffic, and conversion rates, and adjust strategies based on the results to form a closed loop. For example, tools such as Google Search Console and SEMrush can be used to regularly evaluate the effectiveness of SEO strategies and adjust keyword strategies and content strategies based on data. S6: Based on the analysis results of S5, optimize the user experience on mobile devices, improve page loading speed, ensure good performance on mobile devices, and collect optimized performance data for reference Figure 7Specifically, based on the analysis results of S5, the user experience on mobile devices is optimized, the page loading speed is improved, and good performance on mobile devices is ensured. At the same time, the performance data after optimization is collected, including the following steps: S61: Responsive design: Ensure that the website can provide consistent and excellent user experience on different devices. For example, you can use front-end frameworks such as Bootstrap and Foundation to implement responsive design to ensure that the "Family Travel Destination Recommendation" page can be displayed normally on different devices such as mobile phones and tablets. S62: Page speed optimization: Optimize images, compress codes, use CDN, etc. to improve page loading speed. For example, you can use tools such as ImageOptim and TinyPNG to optimize image size and format; use tools such as Webpack and Gulp to compress codes; use CDN services such as Cloudflare and Akamai to speed up the loading speed of the "Family Travel Destination Recommendation" page. S63: Mobile optimization effect monitoring and adjustment: Monitor the user experience and page loading speed on mobile devices, optimize the mobile strategy based on the results, and form a closed loop. For example, you can use tools such as Google PageSpeedInsights and GTmetrix to monitor the page loading speed and user experience on mobile devices, and optimize the mobile strategy based on the data. S7: Explore and apply the latest technologies, including AI and big data analysis, to enhance the innovation and competitiveness of products or services, and collect data on the effects of technology applications for reference Figure 8 Specifically, explore and apply the latest technologies, including AI and big data analysis, to enhance the innovation and competitiveness of products or services, and collect data on the effects of technology applications, including the following steps: S71: AI generates meta descriptions: Use AI technology to automatically generate attractive meta descriptions to increase click-through rates. For example, you can use AI writing tools such as GPT-3 and Jasper to automatically generate meta descriptions that meet SEO specifications, such as "Explore the best family travel destinations - Book now." S72: Intelligent content updates: Based on real-time data analysis, automatically update content to ensure the timeliness and relevance of website content. For example, you can use technologies such as RSS Feed and Webhook to obtain the latest content data in real time and automatically update the content of the "Family Travel Destination Recommendation" page. S73: Technology application effect monitoring and optimization: Evaluate the application effects of AI and innovative technologies, adjust technical strategies based on the results, and form a closed loop. For example, you can use tools such as Google Analytics and SEMrush to evaluate the effects of AI-generated meta descriptions and intelligent content updates, and adjust technical strategies based on data. S8: Establish a continuous monitoring mechanism to track the effects of all steps, iterate and optimize according to market changes and user feedback, and form a closed loop reference Fig. 9Specifically, a continuous monitoring mechanism is established to track the effects of all steps, and iterative optimization is performed according to market changes and user feedback to form a closed loop, including the following steps: S81: SEO effect monitoring: Regularly evaluate the effects of SEO strategies, including indicators such as keyword rankings, traffic, and conversion rates. For example, tools such as Google Search Console and SEMrush can be used to regularly evaluate the effects of SEO strategies. S82: Strategy iteration optimization: According to the monitoring results, the SEO strategy is continuously optimized to ensure the innovation and effectiveness of the strategy. For example, the keyword strategy can be adjusted according to changes in keyword rankings; the content strategy can be optimized according to changes in traffic. S83: Overall strategy effect monitoring and iteration: Comprehensively evaluate the overall effect of the SEO strategy, iterate the strategy according to the results, and form a closed loop. For example, a KPI dashboard can be used to comprehensively evaluate the overall effect of the SEO strategy and adjust the overall strategy according to the data. Example 2 The difference between this embodiment and the above embodiment is that it focuses on integrating all the data collected in S1 to S4, conducting in-depth analysis, identifying trends and problems, and adjusting keywords, content, links, and user experience strategies to improve the importance of the overall effect module, especially the combination of real-time data analysis and predictive analysis, so as to more effectively respond to market changes and user needs. S51: Real-time data analysis and predictive analysis Specifically, real-time data analysis uses real-time data analysis tools to quickly respond to market changes and user needs and adjust SEO strategies. For example, tools such as Google Data Studio and Tableau can be used to monitor the data performance of the "Family Travel Destination Recommendation" page in real time and adjust SEO strategies in a timely manner. Predictive analysis uses machine learning algorithms to predict future search trends and user behaviors and optimize website content and structure in advance. For example, time series prediction models such as ARIMA and LSTM can be used to predict future search trends and user behaviors, and make corresponding preparations in advance, such as optimizing the content of the "Family Travel Destination Recommendation" page in advance before the peak season. Example 3 The difference between this embodiment and the above embodiment is that it focuses on formulating link strategies based on the user behavior data collected in S3, enhancing the network visibility and user engagement of the content, and collecting the importance of link effect data modules, especially the application of personalized recommendation systems, to improve user satisfaction and loyalty. S41: Personalized recommendation system Specifically, the personalized recommendation system provides personalized content recommendations based on user historical behavior and preferences to increase user stickiness. For example, recommendation algorithms such as Collaborative Filtering and Content-Based Filtering can be used to push the latest content related to "family travel destination recommendations" based on the user's historical browsing history and interests.Example 4 The difference between this example and the above examples is that it focuses on the analysis results of S5, optimizes the user experience on mobile devices, improves the page loading speed, ensures good performance on mobile devices, and collects the importance of optimized performance data modules, especially the application of responsive design and page speed optimization, to improve the user experience on mobile devices. S61: Responsive design and page speed optimization Specifically, responsive design ensures that the website can provide a consistent and excellent user experience on different devices. For example, you can use front-end frameworks such as Bootstrap and Foundation to implement responsive design to ensure that the "Family Travel Destination Recommendation" page can be displayed normally on different devices such as mobile phones and tablets. Page speed optimization optimizes images, compresses code, uses CDN, etc. to improve page loading speed. For example, you can use tools such as ImageOptim and TinyPNG to optimize image size and format; use tools such as Webpack and Gulp to compress code; use CDN services such as Cloudflare and Akamai to speed up the loading speed of the "Family Travel Destination Recommendation" page. Example 5 The difference between this example and the above examples is that it focuses on exploring and applying the latest technologies, including AI and big data analysis, to enhance the innovation and competitiveness of products or services, while collecting the importance of technology application effect data modules, especially the application of AI-generated meta descriptions and intelligent content updates to improve the website's click-through rate and content timeliness. S71: AI-generated meta descriptions and intelligent content updates Specifically, AI-generated meta descriptions use AI technology to automatically generate attractive meta descriptions to increase click-through rates. For example, AI writing tools such as GPT-3 and Jasper can be used to automatically generate meta descriptions that meet SEO specifications, such as "Explore the best family travel destinations—book now." Intelligent content updates are based on real-time data analysis to automatically update content to ensure the timeliness and relevance of website content. For example, technologies such as RSS Feed and Webhook can be used to obtain the latest content data in real time and automatically update the content of the "Family Travel Destination Recommendations" page.

[0015] The present application also discloses a readable storage medium, which stores a computer program, and when the computer program is executed by a processor, it implements a search engine optimization method based on big data. By adopting the above technical solution, the readable storage medium can store and execute a search engine optimization method based on big data, covering the determination of innovative keywords through market and user demand analysis, positioning for projects or products, creating high-quality content based on the keywords determined in S1, and optimizing to improve user appeal and search engine rankings, collecting data by analyzing user behavior on products or content, understanding user needs and preferences, and providing a basis for subsequent link strategies and data analysis, formulating link strategies based on user behavior data collected in S3, enhancing the network visibility and user engagement of content, and collecting link effect data at the same time, integrating all data collected in S1 to S4, and conducting in-depth Analyze, identify trends and problems, adjust keywords, content, links and user experience strategies to improve the overall effect, optimize the user experience on mobile devices based on the analysis results of S5, improve page loading speed, ensure good performance on mobile devices, and collect optimized performance data, explore and apply the latest technologies, including AI and big data analysis, to enhance the innovation and competitiveness of products or services, and collect technology application effect data and establish a continuous monitoring mechanism to track the effects of all steps, iterate and optimize according to market changes and user feedback, form a closed loop, etc., so as to comprehensively improve the search engine ranking and user experience of the website and ensure the effectiveness and sustainability of the SEO strategy. The above are all preferred embodiments of the present application, and the protection scope of the present application is not limited thereto. Therefore, any equivalent changes made according to the structure, shape, and principle of the present application should be covered within the protection scope of the present application.

Claims

1. A search engine optimization method based on big data, characterized in that: include: S1: Determine innovation keywords and position the project or product through market and user demand analysis; S2: Create high-quality content based on the keywords identified in S1 and optimize it to increase user appeal and search engine rankings; S3: Collect data and understand user needs and preferences by analyzing user behavior on products or content, providing a basis for subsequent linking strategies and data analysis; S4: Based on the user behavior data collected in S3, formulate link strategies to enhance the network visibility and user engagement of the content, and collect link performance data; S5: Integrate all the data collected in S1 to S4, conduct in-depth analysis, identify trends and problems, and adjust keywords, content, links and user experience strategies to improve overall results; S6: Based on the analysis results of S5, optimize the user experience on mobile devices, improve page loading speed, ensure good performance on mobile devices, and collect optimized performance data; S7: Explore and apply the latest technologies, including AI and big data analysis, to enhance the innovation and competitiveness of products or services, while collecting data on the effectiveness of technology applications; S8: Establish a continuous monitoring mechanism to track the effectiveness of all steps, perform iterative optimization based on market changes and user feedback, and form a closed loop.

2. The search engine optimization method based on big data according to claim 1, characterized in that: Determine innovative keywords and position the project or product through market and user demand analysis The following steps are included: S11: Semantic keyword analysis: Use NLP tools to deeply analyze the semantic associations of keywords, identify potential synonyms and related words, and build a comprehensive keyword library; S12: Keyword trend prediction: Use AI technology to predict keyword trends and dynamically adjust keyword strategies; S13: Keyword layout optimization: Reasonably distribute keywords in the website's meta tags, URLs, and content to ensure that keywords are naturally integrated and avoid stacking; S14: Keyword effect monitoring and adjustment: Regularly evaluate keyword rankings and traffic, adjust keyword strategies based on the results, and form a closed loop.

3. The search engine optimization method based on big data according to claim 1, characterized in that: Based on the keywords identified in S1, create high-quality content and optimize it to improve user appeal and search engine rankings The following steps are included: S21: AI-assisted content creation: combining AI tools and professional editors to generate high-quality, original content to ensure the accuracy and attractiveness of the content; S22: Content structure optimization: using title tags, lists, paragraphs, etc. to make the content structure clear, easy for search engines to understand, and improve user experience; S23: Content personalization: using AI to analyze user preferences, optimize content form and style, and provide personalized content; S24: Content effectiveness monitoring and optimization: Evaluate the content’s reading volume, sharing volume, and user feedback, and optimize content strategies based on the results to form a closed loop.

4. The search engine optimization method based on big data according to claim 1, characterized in that: By analyzing user behavior on products or content, collecting data, understanding user needs and preferences, and providing a basis for subsequent linking strategies and data analysis The following steps are included: S31: Intelligent optimization of internal links: Automatically identify and optimize the internal link structure through algorithms to ensure that the link logic between the internal pages of the website is clear; S32: Improvement of external link quality: Use big data analysis to evaluate the quality and relevance of external links to ensure that the acquired links come from authoritative and relevant websites; S33: Exploration of link building channels: Explore new link building channels, such as industry forums, social media, etc., to enhance the authority of the website; S34: Link effect monitoring and adjustment: Monitor the source and quality of links, adjust the link strategy according to the results, and form a closed loop.

5. The search engine optimization method based on big data according to claim 1, characterized in that: According to the user behavior data collected in S3, a link strategy is formulated to enhance the network visibility and user engagement of the content, while collecting link effect data The following steps are included: S41: Personalized recommendation system: based on user historical behavior and preferences, provide personalized content recommendations to increase user stickiness; S42: User behavior modeling: Use big data to analyze user behavior patterns on the website, optimize website layout and content, and improve user satisfaction; S43: AI predicts user behavior: Use AI to predict user behavior and optimize user experience in advance; S44: User behavior monitoring and optimization: Continuously monitor user behavior and optimize user experience strategies based on the results to form a closed loop.

6. The search engine optimization method based on big data according to claim 1, characterized in that: The integration of all data collected in S1 to S4, in-depth analysis, identification of trends and issues, and adjustment of keywords, content, links, and user experience strategies to improve overall effectiveness includes the following steps: S51: Real-time data analysis: using real-time data analysis tools to quickly respond to market changes and user needs and adjust SEO strategies; S52: Predictive analysis: Use machine learning algorithms to predict future search trends and user behaviors, and optimize website content and structure in advance; S53: Strategy effect monitoring and iteration: Regularly evaluate the effectiveness of SEO strategies, including keyword rankings, traffic, conversion rates and other indicators, adjust strategies based on the results, and form a closed loop.

7. The search engine optimization method based on big data according to claim 1, characterized in that: The analysis results based on S5 are used to optimize the user experience on mobile devices, improve the page loading speed, ensure good performance on mobile devices, and collect the optimized performance data, including the following steps: S61: Responsive design: ensure that the website can provide a consistent and excellent user experience on different devices; S62: Page speed optimization: optimize images, compress codes, use CDN, etc. to improve page loading speed; S63: Mobile optimization effect monitoring and adjustment: monitor the user experience and page loading speed on mobile devices, and optimize the mobile strategy according to the results to form a closed loop.

8. The search engine optimization method based on big data according to claim 1, characterized in that: The exploration and application of the latest technologies, including AI and big data analysis, to enhance the innovation and competitiveness of products or services, while collecting data on the effects of technology application, includes the following steps: S71: AI generates meta descriptions: Use AI technology to automatically generate attractive meta descriptions to increase click-through rates; S72: Intelligent content updates: Based on real-time data analysis, automatically update content to ensure the timeliness and relevance of website content; S73: Technology application effect monitoring and optimization: Evaluate the application effects of AI and innovative technologies, adjust technical strategies based on the results, and form a closed loop.

9. The search engine optimization method based on big data according to claim 1, characterized in that: The above mentioned mechanism of continuous monitoring is established to track the effects of all steps, and iteratively optimize according to market changes and user feedback to form a closed loop. The following steps are included: S81: SEO effectiveness monitoring: Regularly evaluate the effectiveness of SEO strategies, including keyword rankings, traffic, conversion rates and other indicators; S82: Strategy iteration optimization: Based on the monitoring results, continuously optimize the SEO strategy to ensure the innovation and effectiveness of the strategy; S83: Overall strategy effect monitoring and iteration: Comprehensively evaluate the overall effect of the SEO strategy, iterate the strategy based on the results, and form a closed loop.

10. A readable storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is executed by a processor, the search engine optimization method based on big data described in any one of claims 1 to 9 is implemented.

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